{"id":"W3115357095","doi":"10.1111/ina.12782","title":"Quantitative filter forensics: Size distribution and particulate matter concentrations in residential buildings","year":2020,"lang":"en","type":"article","venue":"Indoor Air","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"","keywords":"ASHRAE 90.1; Filtration (mathematics); Environmental science; Volume (thermodynamics); Filter (signal processing); Particulates; HVAC; Ventilation (architecture); Particle-size distribution; Aerosol; Particle (ecology); Particle size; Settling; Materials science; Analytical Chemistry (journal); Air conditioning; Environmental engineering; Chemistry; Statistics; Meteorology; Mathematics; Chromatography; Physics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005637328,0.0002841704,0.0001495297,0.001473867,0.0005379426,0.000580553,0.0004063178,0.0003668232,0.0004530272],"category_scores_gemma":[0.0008188639,0.0001330691,0.0001297415,0.001032804,0.0005278901,0.000328546,0.000288258,0.0001443655,0.0001579989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00185804,"about_ca_system_score_gemma":0.0006475914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1556939,"about_ca_topic_score_gemma":0.2190859,"domain_scores_codex":[0.9994173,0.00006755072,0.00002158507,0.0001201904,0.0003103927,0.00006303365],"domain_scores_gemma":[0.9994844,0.0000680603,0.0001428193,0.00003505349,0.0002392273,0.00003031914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002108476,0.0001294343,0.8656222,0.0001194056,0.00007439106,0.0003556404,0.001950229,0.003070413,0.09686004,0.000262787,0.0004646071,0.03088006],"study_design_scores_gemma":[0.00000269552,0.0001540239,0.9677387,0.00001155177,0.00001878338,0.000360111,0.0009716614,0.003690787,0.02602597,0.0000894261,0.0009194721,0.00001671891],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974021,0.00008744435,0.001488682,0.00001407565,0.000001359572,0.00001361618,0.0003426982,0.00002151018,0.0006286433],"genre_scores_gemma":[0.9980296,0.00006380855,0.001277124,0.00000968909,0.000002407648,0.000005081048,0.0002450375,0.000004085089,0.000363057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1556939,"threshold_uncertainty_score":0.3095754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03351563440236982,"score_gpt":0.2974053056321297,"score_spread":0.2638896712297599,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}